Cardiac rhythm analysis is commonly performed from electrogram signals (EGM) collected by electrodes located on endocardial leads implanted in the myocardium to measure the atrial and/or ventricular depolarization potential. These EGM signals are analyzed by the device, which delivers to the patient if necessary an appropriate therapy in the form of low energy stimulation pulses (for bradycardia pacing or resynchronization of the ventricles) or high energy defibrillation shocks.
The cardiac rhythm analysis, and therefore the decision whether or not to deliver a therapy, however, can be affected by artifacts collected by the endocardial lead. These artifacts can have various origins. A first series of artifacts corresponds to situations where the device not only detects the cardiac event itself, e.g., a wave of depolarization of the cavity in question, but also a disturbance associated with this event and wrongly considered as another depolarization event that occurred after the first, for example, a late depolarization wave, crosstalk detected between different heart cavities, and far-field signal detection.
A second series of artifacts, which are the subject of the present invention, are the artifacts from extrinsic noise and not related to a depolarization of the myocardium. This noise can have many origins, including, for example, the myopotentials associated with muscle contractions, electromagnetic interference (EMI) from electronic surveillance equipment, electrical devices located nearby, electrosurgical instruments, communication systems, and the like.
In addition, the digital signal processing (“DSP”) units typically used in active implantable medical device generate a certain noise level, which is added to the signal depolarization. In particular, the digital filtering can initially increase the amplitude of the signal oscillations before the amplitude slowly decreases as the system stabilizes over time, with the consequence of disrupting the analysis carried out downstream of this distorted signal.
In general, a noise that is present with varying regularity, whether extrinsic or due to the specific digital processing, can be interpreted by the device as a depolarization of the myocardium, with the risk of generating inappropriate therapy, such as wrongly inhibiting the bradycardia pacing or the resynchronization pacing, or conversely, by falsely delivering inappropriate shocks.
Various techniques have been proposed to reduce the impact of extrinsic noise, including the upstream application to the signal processing circuits for analog or digital filtering, the introduction of refractory periods, the automatic adjustment of the sensitivity of the detection amplifiers, or the automatic gain control of these amplifiers.
EP 0958843 A1 describes one technique of “autosensing”, wherein an algorithm continuously adapts the detection threshold depending on the level of noise and the amplitude of the EGM signals associated with detected cardiac events. However, the use of these autosensing methods is always at the expense of a good detection. In particular, to detect ventricular fibrillation (VF), the signal level of which is considered relatively low, it is necessary to have a maximum sensitivity, in order to prevent failing to detect events that should have been detected. But the signal amplitude of ventricular fibrillation (specifically, QRS complexes indicative of ventricular depolarizations) may be of a variable level, between the noise signal level and the signal level corresponding to a sinus complex (a spontaneous depolorization).
Consequently, setting a threshold low enough to detect ventricular fibrillation runs the inevitable risk of also detecting a possible noise. If in addition there is a regular noise, for a patient with normal sinus heart rhythm, this noise can be confused with depolarizations. This may distort the evaluation of the average cardiac rate as determined by the device, with an (incorrectly) estimated rate of a level much higher than reality, and a corresponding risk of applying undesirable antitachycardia therapy (a false positive situation, called “oversensing”).
Conversely, if the device is programmed to a too low sensitivity value, that is to say, with a too high detection threshold, the actual episodes of ventricular fibrillation may not be detected (a false negative situation, called “undersensing”) with potentially serious consequences for the patient.
With the detection of extrinsic noise being usually inevitable, the problem addressed by the present invention is to distinguish these noises from the actual heart depolarizations, in order to avoid triggering inappropriate therapies and, conversely, inhibiting delivery of therapies that if delivered would have been appropriate.
The identification of these noises and their mitigation by means of filters is a complex task, the main difficulty being the extreme variability of these spurious signal components, which implies relatively complex processing to be effective.
Complex digital processing techniques have been proposed for this purpose to ensure the detection of a QRS complex in the endocardial signal, including, for example, non-linear filtering, wavelet transform, artificial network, genetic algorithm and linear prediction techniques. These various, complex, algorithms require a large number of arithmetic operations and require significant computing resources, with a further significant increase in energy consumption by the device, consequently having an impact on the useful life of the implanted device.
Another technique, described, for example, in EP 0775502 and its counterpart U.S. Pat. No. 5,836,980 (both assigned to Sorin CRM S.A.S, previously known as ELA Medical), is to analyze the signal characteristics by deriving it by differentiating means to assess the instantaneous variations of the signal by comparing them to predetermined thresholds. The required circuits are relatively simple but, however, they enable a relatively limited discrimination in the case of highly noisy signals.
Yet another technique was proposed by EP 1857142 A1 and its counterpart U.S. Pat. Publication No. 2007/0282379 (both assigned to Sorin CRM S.A.S., previously known as ELA Medical), which is to conduct a double detection by analysis of the depolarization of the EGM electrical signal, and of the contraction of the myocardium by measuring the endocardial acceleration (EA), the latter obtained via an accelerometer in direct contact with the heart muscle. In the presence of noises, the device operates an alarm verification to confirm that the detected signal has actually been followed by a mechanical activity of the heart and thus constitutes a signal of depolarization (QRS complex) and not an artifact. In this regard, the depolarization is an electrical phenomenon sensitive to noise and is indeed usually followed by cardiac contraction, a mechanical phenomenon that is not affected by the same noise.
But this presupposes to have a lead equipped with an endocardial acceleration sensor, and if the patient already has an implanted device, implies during a change in the generator to change not only the generator but also the lead, which is a much more difficult surgery.
EP 0429025 A2 describes a technique to make a double discrimination, both on the amplitude and on the width of the peaks of detected signal: a first amplitude discrimination is used to extract only signals exceeding a given level, while the analysis of the width of the signal being above this threshold amplitude discriminates a possible parasitic component that would not have been eliminated in the filtering upstream of this processing. U.S. Pat. No. 4,000,461 describes a comparable technique of discrimination by amplitude/duration cross-analysis of the peaks of detected signal. The thresholds for comparison (amplitude and width) are adjustable, and adjusted to a value chosen by the practitioner during the programming of the device. This presupposes, however, that the conditions at the time of adjustment remain fairly constant over time, for an effective discrimination. But in practice this is rarely the case, making this technique unreliable for detecting the presence (or not) of a QRS complex in the received endocardial signal, especially to detect ventricular fibrillation for which, as explained above, the useful signal can be at a variable level, intermediate between the noise and the signals of the sinus complexes. Because of the fixed parameters, the risks of oversensing or undersensing are then particularly high, with the potential serious consequences that have been outlined above.